Battery improvement is one of the most promising emerging areas where quantum computing can make a difference, and today we’re announcing a significant milestone that should help scientists and researchers to design more efficient and higher performing electric batteries to power our collective future.
Developing a quantum computing algorithm to build a better electric car battery
There are some 250 million vehicles on the road in the U.S. alone, and fewer than 1% of those are electric. Increasing the proportion of electric vehicles can play a significant role in improving air quality and reducing the greenhouse gas emissions that lead to global warming.
To achieve this, researchers are working hard to reduce the cost of electric batteries, extend their useful life and address safety concerns related to overheating. But achieving breakthroughs has been difficult because of limitations with the classical computers used to model and understand battery chemistry.
Working with our partners at Hyundai and other research institutes, researchers at IonQ have developed a quantum algorithm that runs efficiently on our trapped-ion quantum computing hardware and should eventually help scientists develop new and improved types of electric batteries. Our research paper describing this work was published this week.
Accurate Modeling of Chemical and Electrical Reactions
One of the biggest challenges in battery development is accurately modeling the complex chemical and electrical reactions that occur inside electronic batteries. Classical computers are used for this work today but are greatly limited in the number of electrons they can model to produce accurate predictions for new designs.
The new quantum algorithm our researchers developed can simulate the molecules involved in the lithium-air reactions that occur within lithium-ion batteries. The algorithm is highly efficient and can yield qualitatively correct predictions that should eventually help battery engineers to understand the configuration of molecules, their energy profile and how they react. This in turn should allow them to improve the efficiency of current batteries and develop next-generation battery types.
The efficiency of the algorithm is only possible with IonQ's trapped ion quantum computers, because it takes advantage of our native gates and the all-to-all connectivity design of our quantum systems. The high fidelity of our quantum technology allows us to achieve an excellent match between theory and experiments.
Hybrid Quantum-classical Computing Design
For maximum efficiency, our work takes advantage of a hybrid quantum-classical computing design, making clever choices about which parts of the algorithm are run on which type of computer. This allows us to achieve the best possible performance from both quantum and classical computers.
The benefits of this work are not limited to electric batteries, since the ability to model molecules and electrons at scale is also invaluable for drug development, climate modeling and many other critical areas of scientific work. This latest breakthrough is another example of the wide range of important real-world challenges that quantum computers are being used to address.
The latest work builds on an existing multi-year partnership between IonQ and Hyundai. In addition to battery development, we are also working with Hyundai on a project to use quantum computing to improve object detection for improved road safety.
To learn more, read the full press release here.
The research paper was authored by Luning Zhao, Joshua Goings, Sonika Johri, Kenneth Wright and Jason Nguyen of IonQ; Kyujin Shin and Woomin Kyoung of the Materials Research & Engineering Center, R&D Division, Hyundai Motor Company; Johanna I. Fuks and June-Koo Kevin Rhee, Qunova Computing; and Young Min Rhee, from the Department of Chemistry at the Korea Advanced Institute of Science & Technology (KAIST).